Triple
T63030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armor Branch |
E1250
|
entity |
| Predicate | engagementType |
P3663
|
FINISHED |
| Object | offensive operations |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: offensive operations | Statement: [Armor Branch, engagementType, offensive operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagementType Context triple: [Armor Branch, engagementType, offensive operations]
-
A.
notableEngagement
Indicates a significant interaction, involvement, or participation between entities that is noteworthy or distinguished in some context.
-
B.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
C.
obligationType
Indicates the specific kind or category of duty, requirement, or commitment that applies within an obligation relationship.
-
D.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or activity.
-
E.
ceremonyType
Indicates the specific kind or category of ceremony associated with an event or relationship.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea3c44081908fa3856969881d1f |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24fcf5a88819088c5fa4c08476358 |
completed | Feb. 28, 2026, 2:15 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.